forked from mindspore-Ecosystem/mindspore
49 lines
1.5 KiB
Python
49 lines
1.5 KiB
Python
# Copyright 2022 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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""" test_unbind """
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import numpy as np
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import pytest
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from mindspore import context, Tensor
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from mindspore import nn
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class UnbindNet(nn.Cell):
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def construct(self, x, dim):
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return x.unbind(dim)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.platform_arm_cpu
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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@pytest.mark.parametrize('mode', [context.GRAPH_MODE, context.PYNATIVE_MODE])
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def test_unbind(mode):
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"""
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Feature: unbind
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Description: Verify the result of unbind
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Expectation: success
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"""
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context.set_context(mode=mode)
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x = Tensor(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]))
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dim = 0
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unbind = UnbindNet()
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output = unbind(x, dim)
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for i in range(len(x)):
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assert np.allclose(output[i].asnumpy(), x[i].asnumpy(), rtol=0.0001)
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